This paper presents one of the outcomes of a
research project concerned with the development of a method for
synthesizing, under controlled conditions in the laboratory, the
random vibrations generated by road transport vehicles. It
addresses some of the deficiencies and limitations of current
random vibration synthesis methods used for evaluating and
validating the performance of packaging systems. The paper
deals with the development of a technique for decomposing
non-stationary random vibration signals into constituent
Gaussian elements. The hypothesis that random non-stationary
vehicle vibrations are essentially composed of a sequence of
zero-mean random Gaussian processes of varying standard
deviations is tested and the paper reveals that the variations in the
magnitude of the vibrations are the cause of the leptokurtic,
non-Gaussian nature of the process. It is shown how
non-stationary vibration signals can be systematically
decomposed into these independent random Gaussian elements by
means of a numerical curve-fitting procedure. The paper
describes the development of the algorithm which is designed to
automatically extract the parameters of each constituent
Gaussian process namely the RMS level and the Vibration Dose.
The validity of the Random Gaussian Sequence Decomposition
(RGSD) method was tested using a set of road vehicle vibration
records and was found to be capable of successfully extract the
Gaussian estimates as well as the corresponding Vibration Doses.
Validation was achieved by comparing the sum of these Gaussian
estimates against the PDF of the original vibration record. All validation cases studied show that the RGSD algorithm is very
successful in breaking-down non-stationary random vibration
records into their constituent Gaussian processes. Finally, the
significance and relevance of this technique with respect to the
synthesis of non-stationary vibrations for package evaluation and
validation purposes is highlighted.